code: def test_batch_sizes(self) -> None:
      for dataloader in self.dataloaders:
          batch_sizes = []
          for x, _y in dataloader:
              batch_sizes.append(x.shape[0])
  
          self.assertGreater(len(set(batch_sizes)), 1)
          self.assertAlmostEqual(
              np.mean(batch_sizes),
              self.batch_size // self.world_size,
              delta=2,
          )
  
file_path: opacus/opacus/tests/distributed_poisson_test.py
imports: import unittest
  import numpy
  import torch
  from opacus.utils.uniform_sampler import DistributedUniformWithReplacementSampler
label_desc: Use image node_id 4 for calling the PoissonSamplingTest obj's underlying member method code with example usage: obj.test_batch_sizes() without return types